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Mathematical techniques used in minimum variance orbital navigation and guidance, midcourse phase, lunar parking, descent orbits, landing, ascent, and rendezvous
The inclinations of the neutral line at the ecliptic plane derived from source surface model maps of coronal fields are measured for the interval from June 1976 to March 1992. The mean and median values of 53 deg and 57 deg are close to the average inclinations determined earlier from minimum variance analyses of solar wind measurements at sector boundaries, but the mode falls in the 80 deg - 90 deg bin. This result, which is based on the model assumptions implicit in deriving the source surface maps, predicts that the heliospheric current sheet typically intersects the ecliptic plane nearly at right angles, even without steepening by stream interaction regions. High inclinations dominate the solar cycle for about 7 years around solar maximum. Dips to lower inclination occur near solar minimum, but high variance admits a wide range of inclinations throughout the cycle. Compared to the smooth solar cycle variation of the maximum latitudinal excursion of the neutral line, often treated as the tilt angle of a flat heliospheric current sheet, the noisy variation of the inclinations reflects the degree to which the neutral line deviates from a sine wave, implying warps and corrugations in the current sheet. About a third of the time the neutral line so deviates that it doubles back in longitude.
The design of an optimal dynamic compensator for a multivariable discrete time system is studied. Also the design of compensators to achieve minimum variance control strategies for single input single output systems is analyzed. In the first problem the initial conditions of the plant are random variables with known first and second order moments, and the cost is the expected value of the standard cost, quadratic in the states and controls. The compensator is based on the minimum order Luenberger observer and it is found optimally by minimizing a performance index. Necessary and sufficient conditions for optimality of the compensator are derived. The second problem is solved in three different ways; two of them working directly in the frequency domain and one working in the time domain. The first and second order moments of the initial conditions are irrelevant to the solution. Necessary and sufficient conditions are derived for the compensator to minimize the variance of the output.
The dynamic structure of large-amplitude Alfven disturbances of the interplanetary magnetic field is examined by transforming one-hour intervals of Explorers 33 and 35 magnetometer data from the solar ecliptic coordinate system to a coordinate system defined by the principal axes of the variance matrix. It is demonstrated how some interplanetary magnetic field fluctuations observed by both Explorers are consistent with local properties theoretically predicted for plane large-amplitude Alfven waves by Barnes and Hollweg (1974). The different types of angular motion of the magnetic field component normal to the direction of minimum variance may be indicative of the detailed conditions of the solar coronal plasma in the regions generating the Alfven waves, or some aspect of local generation.
Unmanned spacecraft guidance policy and orbit determination, using linear perturbation theory and minimum variance estimation
Minimum variance method for estimating state vector with acceptable accuracy constraints in orbit calculation
Minimum variance simulation for satellite attitude determination reliability using magnetic and solar measurements
Differential equations for minimum variance linear filter separating signals from additive correlated noise, using discrete time optimum formulas
Discrete parameter covariance stationary stochastic process in rotation sampling, deriving minimum variance unbiased linear population mean estimator by constrained optimization procedure
An iterative method, which is characterized as a maximum-likelihood minimum-variance technique, was used to extract the aerodynamic parameters of a Navion airplane from flight data. The purposes were to compare the results with parameters obtained from wind-tunnel tests and with results obtained by analog matching the same data, and to develop techniques for application of the parameter extraction program. Results from the study showed that the parameter-extraction program can produce aerodynamic parameters which will permit close estimation of the aircraft time histories used in the extraction process. The program determined an estimate of the standard deviations of the states and parameters. These estimates were used to indicate how well the calculated states fit the flight data and the confidence in the values of the estimated parameters. The study also showed that the values of the parameters were affected by the data and mathematical model used during the extraction process. Because of the lack of confidence in the parameters extracted by use of some of the sets of data, several parameters were estimated by other methods. By using a combination of methods, a set of parameters which gave a fit to the data was obtained.
A method is proposed for dealing with the divergence phenomenon problem encountered in applications of minimum-variance recursive estimators when the error covariance calculated by the estimator becomes inconsistent with the actual error covariance. The proposed method differs from previous ones in that the state model and statistics are accepted as given. The form of the optimal estimator is used, but a constant check is made on the consistency of the calculated and actual error covariances. The method is independent of the source of error, whether it be inaccuracies in the system model, incorrect values of the a priori and random process statistics, approximations required in the case of nonlinear systems, or computational roundoff. Several simulated examples, in which inconsistencies in the calculated and actual error covariances exist, show a significant improvement in the performance of the estimator when the given procedure is applied.
For life testing procedures, a Bayesian analysis is developed with respect to a random intensity parameter in the Poisson distribution. Bayes estimators are derived for the Poisson parameter and the reliability function based on uniform and gamma prior distributions of that parameter. A Monte Carlo procedure is implemented to make possible an empirical mean-squared error comparison between Bayes and existing minimum variance unbiased, as well as maximum likelihood, estimators. As expected, the Bayes estimators have mean-squared errors that are appreciably smaller than those of the other two.
To determine whether estimation process simulated by linear error analysis will converge, criterion has been developed based on extension of classical observability. Particular application of technique is with groups of batched navigation data where statistics of estimation errors are derived with classical minimum-variance methods.
Statistical retrieval methods for remote sounding are reviewed. Methods are given for constraining an essentially incomplete problem by means of the known statistical behavior of the solution. Information content of the observations and the meteorological structure are discussed. Linear versions of maximum probability and minimum variance methods are given in some detail, and extensions to the nonlinear case are described.
A technique is presented for processing accelerometer data obtained during the AE missions in order to estimate the atmospheric density profile. A minimum variance, adaptive filter is utilized. The trajectory of the probe and probe parameters are in a consider mode where their estimates are unimproved but their associated uncertainties are permitted an impact on filter behavior. Simulations indicate that the technique is effective in estimating a density profile to within a few percentage points.
A smooth empirical Bayes estimator is derived for the intensity parameter (hazard rate) in the Poisson distribution as used in life testing. The reliability function is also estimated either by using the empirical Bayes estimate of the parameter, or by obtaining the expectation of the reliability function. The behavior of the empirical Bayes procedure is studied through Monte Carlo simulation in which estimates of mean-squared errors of the empirical Bayes estimators are compared with those of conventional estimators such as minimum variance unbiased or maximum likelihood. Results indicate a significant reduction in mean-squared error of the empirical Bayes estimators over the conventional variety.
Development of a Bayesian analysis of the scale and shape parameters in the Weibull distribution and the corresponding reliability function with respect to the usual life-testing procedures. For the scale parameter theta, Bayesian estimates of theta and reliability are obtained for the uniform, exponential, and inverted gamma prior probability densities. Bhattacharya's results (1967) for the one-parameter exponential life-testing distribution are reduced to a special case of these results. A fully Bayesian analysis of both the scale and shape parameters is developed by assuming independent prior distributions; since in the latter case, analytical tractability is not possible, Bayesian estimates are obtained through a conjunction of Monte Carlo simulation and numerical-integration techniques. In both cases, a computer simulation is carried out, and a comparison is made between the Bayesian and the corresponding minimum-variance unbiased, or maximum likelihood, estimates. As expected, the Bayesian estimates are superior.
A fully symmetrized multiple scattering series is considered for the description of proton-deuteron elastic scattering. An off-shell continuation of the experimentally known twobody amplitudes that retains the exchange symmeteries required for the calculation is presented. The one boson exchange terms of the two body amplitudes are evaluated exactly in this off-shell prescription. The first two terms of the multiple scattering series are calculated explicitly whereas multiple scattering effects are obtained as minimum variance estimates from the 146-MeV data of Postma and Wilson. The multiple scattering corrections indeed consist of low order partial waves as suggested by Sloan based on model studies with separable interactions. The Hamada-Johnston wave function is shown consistent with the data for internucleon distances greater than about 0.84 fm.